Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

511
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
511
Regression Toward the Mean01:52

Regression Toward the Mean

7.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
7.3K
Study Design in Statistics01:15

Study Design in Statistics

10.2K
A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
10.2K
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

4.0K
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
4.0K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.8K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.8K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

1.1K
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
1.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Linking Lipidomics to Vulnerable Coronary Plaques: A PROSPECT II Substudy.

Arteriosclerosis, thrombosis, and vascular biology·2026
Same author

Contemporary Data on Sex Differences in Coronary Angiography Findings: A Dual-Nation Study.

JACC. Advances·2026
Same author

Left Ventricular Ejection Fraction Trajectory and Long-Term Outcomes Following Percutaneous Coronary Intervention for Myocardial Infarction.

JACC. Advances·2026
Same author

Real-World Usage of a Paclitaxel-Coated Balloon With Urea Compared With Other Contemporary Drug-Coated Balloons: A 2-Year Analysis From SCAAR in Over 6000 Patients.

Journal of the American Heart Association·2026
Same author

Ticagrelor versus clopidogrel in orally anticoagulated patients with acute coronary syndrome undergoing percutaneous coronary intervention.

EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology·2026
Same author

Abbreviated DAPT after PCI with drug coated balloons in acute coronary syndromes - insights from the SWEDEHEART registry.

European heart journal. Cardiovascular pharmacotherapy·2026

Related Experiment Video

Updated: Mar 9, 2026

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.7K

Win statistics applied to registry-based randomized clinical trials.

Rebecca Rylance1, Philippe Wagner2, Matthias Götberg3

  • 1Department of Cardiology, Clinical Sciences, Lund University, Skåne University Hospital, Lund, 221 85, Sweden. rebecca.rylance@med.lu.se.

Trials
|March 7, 2026
PubMed
Summary
This summary is machine-generated.

Win statistics provide a transparent alternative to survival analysis for composite endpoints in clinical trials. This reanalysis confirmed good correspondence between win statistics and hazard ratios, supporting their use in future trial designs.

Keywords:
Composite endpointsCox ph modelHierarchical composite endpointsRegistry-based dataWin oddsWin ratio

More Related Videos

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

1.3K
Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

15.4K

Related Experiment Videos

Last Updated: Mar 9, 2026

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.7K
Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

1.3K
Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

15.4K

Area of Science:

  • Biostatistics
  • Clinical Trials
  • Survival Analysis

Background:

  • Traditional survival analysis often uses hazard ratios for composite endpoints.
  • Win statistics offer an alternative method for analyzing such endpoints.
  • This study re-analyzed registry-based randomized controlled trials using win statistics.

Purpose of the Study:

  • To evaluate the correspondence between win statistics and hazard ratios in previously published trials.
  • To assess the transparency, scientific rigor, and validation potential of win statistics.
  • To explore win statistics as an alternative to traditional survival analysis for composite endpoints.

Main Methods:

  • Win statistics hierarchically ordered events by clinical importance (e.g., death, myocardial infarction).
  • Compared each treatment patient against each control patient in hierarchical order.
  • Calculated win odds, incorporating ties, as an extension of win statistics.

Main Results:

  • Win statistics showed good correspondence with previously reported hazard ratios across multiple trials (TASTE, iFR-SWEDEHEART, DETO2X-AMI, VALIDATE).
  • Results for the TASTE trial were neutral for both hazard ratio and win odds.
  • The IAMI trial demonstrated improved outcomes for the vaccinated group using both methods.

Conclusions:

  • Win statistics offer a viable alternative to survival analysis for composite endpoints.
  • This method allows hierarchical evaluation of multiple clinical events, providing a comprehensive view of treatment efficacy.
  • This study represents the first multi-registry trial reanalysis using win statistics.